Predict the future of your business with Predictive Analysis

Predictive Analysis has infused a new sense to raw/natural underlying customer data, which earlier ended up as being mere records in company data records and spreadsheets. Lately with Artificial Intelligence and Machine learning, we witnessed how this customer data is turned into a heap of insights to create pin-point targeted marketing campaigns and forecasting, a customer's need sometimes even before he knows, this is called Predictive Analysis. Looking at the recent trends, Predictive Analysis is evolving from forecasting marketing campaigns to driving the annual business strategy of enterprises.

 Airlines use Predictive Analysis to set the pricing of the tickets depending on the traffic forecast, hospitals use it to forecast the readmission cases, insurance companies and banks use it to predict a potential fraud, ever since the limelight has fallen on big data, Predictive Analysis (PA) has been helping enterprises make incremental gains in various realms.

Return of Investment

Predictive Analysis can help enterprises generate more business by running targeted campaigns, identify potential risks, optimize operational costs. Predictive Analysis makes quantifiable assessments of what lies ahead of a particular decision, if it's a risk or beneficial for the company. These predictions help companies to take preventive and proactive steps rather than mitigative actions. Making better decisions, optimal use of resources, saving cost, and averting risks, these incremental actions cumulatively help a company get maximum return of investment and turn profitable.

Identify False Leads

Predictive Analysis can help you accurately identify whether a lead is passable or potent. Companies waste a huge amount of time and effort chasing false leads, knowing beforehand if the lead is worth chasing saves money also. Based on past purchases, transaction data, and customer behavior, predictive models can precisely categorize promising leads, and companies can take suitable marketing decisions to turn the lead into a likely purchase. 

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It also helps businesses categorize customers in similar categories, for example, a group of customers who will be willing to spend the most amount of money in the form of purchases like a loyal customer, an impulsive customer who purchased the spur of the moment or a discount customer who when engaged with the right discount will make the purchase. It saves a lot of marketing cost for the business because now the company is acting based on clear information and not on instincts

Generating Promising Leads

Based on a report by McKinsey, Predictive Analysis helps companies to improve their lead conversion rate by 30% by doing minor tweaking in their lead generation pipeline. Based on the existing customer database, Predictive models can identify patterns and behavioral traits and find customers who have similar purchase patterns and interest, but still haven't come across your business. This turns out to be a huge help for the sales team, it generates a database of potential new customers whom the sales team can contact with a high possibility of grabbing a deal. This becomes even more important when the number of resources is limited, and companies can make the best utilization of the resources to generate revenue.

These corrective and cumulative results help the company build a more robust foundation for the future, and at the same time generating revenues. Predictive Analysis gives companies the power to know the outcome of a decision even before it is implemented, this future-focused ecosystem drives the business to serve their customers better today. 

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